This patch adds a benchmark to the Swift benchmark suite based on the
ChaCha20 encryption algorithm.
As Swift evolves it is important that it tackles more and more features
and possible use cases. One of these great use-cases is low-level CPU
intensive code, and cryptographic algorithms are a really important
test-bed.
This benchmark therefore provides a real-world test case for Swift's
optimiser. My ideal outcome here is that Swift should be able to perform
as well at this benchmark as a naive equivalent C implementation.
Specifically, I add some benchmarks for weak, unowned, unsafe (unowned), and
unmanaged. The reason for the split in between unsafe (unowned) and unmanaged is
that one is testing the raw compiler features and the other is validating stdlib
performance.
FindStringNaive is a simple benchmark which implements a naive String
finding algorithm that currently shows a lot of ARC traffic, hopefully
to be reduced in the future.
This currently copies the array each time it swaps elements. This
makes it 1500x slower than it should be to sort the array. The
benchmark now runs in 15ms but should be around 10us when fully
optimized.
This algorithm is an interesting optimization problem involving array
optimization, uniqueness, bounds checks, and exclusivity. But the
general first order problem is how to modify a CoW data structure
that's stored in a class property. As it stands, the property getter
retains the class property around the modify accesses that checks
uniqueness.
Added --meta option to log measurement metadata:
* PAGES – number of memory pages used
* ICS – number of involuntary context switches
* YIELD – number of voluntary yields
(Pages and ICS were previously available only in --verbose mode.)
Added support for running benchmarks using substring filters. Positional arguments prefixed with a single + or - sign are interpreted as benchmark name filters.
Excecutes all benchmarks whose names include any of the strings prefixed with a plus sign but none of the strings prefixed with a minus sign.
Support for gathering a minimal number of samples per benchmark, using the optional `--min-samples` argument, which overrides the automatically computed number of samples per `sample-time` if this is lower.
adds a benchmark that imitates SwiftNIO's ChannelPipeline. Recently,
Swift master regressed on this benchmark, therefore I believe adding it
to Swift provides value as it seems to be different enough to the existing
benchmarks.
Generalize CSVParsing so that it can be ran across all of String's
views, and add corresponding benchmarks.
Note: This does change the profile of the original benchmark, which
was an odd mixture of String and UTF16View.
Now one can on Darwin/Linux build the benchmarks via swiftpm from build-script by passing in:
```
build-script $NORMAL_ARGS --install-swift --install-swiftpm --install-llbuild --toolchain-benchmarks --swiftpm --llbuild
```
This is done using the infrastructure that BenL added for sourcekit-lsp.
Lowered the default sample cap from 2k to 200. (This doesn’t effect manually specified `--num-samples` argument in the driver.)
Swift benchmarks have pretty constant performance profile over time. It’s more beneficial to get multiple independent measurements faster, than more samples from the same run.
